ENCODING UNIQUE GLOBAL MINIMA IN NESTED NEURAL NETWORKS

被引:2
作者
BARAM, Y [1 ]
机构
[1] NASA,AMES RES CTR,MOFFETT FIELD,CA 94035
关键词
NEURAL NETWORKS; NESTING; SPARSITY; CODING; GLOBAL MINIMA;
D O I
10.1109/18.87008
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Nested neural networks are constructed from outer products of patterns over {-1,0,1}N, whose nonzero bits define subnetworks and the subcodes stored in them. The set of permissible words, which are network-size binary patterns composed of subcode words that agree in their common bits, is characterized and their number is derived. It is shown that if the bitwise products of the subcode words are linearly independent, the permissible words are the unique global minima of the Hamiltonian associated with the network.
引用
收藏
页码:1158 / 1162
页数:5
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